A system for selecting images of an event indicator includes a processor and a memory storing instructions which, when executed, cause the system to: access images of a portion of a gastrointestinal tract captured by a capsule endoscopy device; for each of the images, access one or more scores indicating a presence of an event indicator; select seed images from among the images based on the one or more scores; deduplicate the seed images for images showing the same occurrence of the event indicator, where the deduplicating utilizes a consecutive-image tracker; and present the deduplicated seed images in a graphical user interface to display potential occurrences of the event indicator.

The present invention relates to the field of medical monitoring, and, in particular, to non-contact detecting and monitoring of patient breathing. Systems, methods, and computer readable media are described for calculating a change in depth of a region of interest (ROI) on a patient and assigning one or more visual indicators to at least a portion of a graphic based on the calculated changes in depth and/or based on a tidal volume signal generated for the patient. In some embodiments, the systems, methods, and/or computer readable media can display the visual indicators overlaid onto at least the portion in real-time and/or can display the tidal volume signal in real-time. The systems, methods, and/or computer readable media can trigger an alert and/or an alarm when a breathing abnormality is detected.

An image processing apparatus contains an input unit to input a fluorescent image and a morphological image of a tissue. A biological substance expressed at a first structure of a cell in the tissue is stained by a fluorescent substance. The fluorescent image illustrates a fluorescent bright point which represents expression of the biological substance. The morphological image illustrates a morphology of a second structure of a cell in the tissue and contains the same range of the tissue as the fluorescent image. The apparatus further contains a feature amount extraction unit to extract a feature amount of the second structure from the morphological image, a bright point extraction unit to extract the fluorescent bright point from the fluorescent image, and a region of interest determination unit to determine a region of interest based on the feature amount of the second structure and a distribution of the fluorescent bright point.

Apparatus and methods are described for use with an endoluminal device that includes one or more radiopaque portions and that moves through a lumen of a subject. A sequence of radiographic images of a portion of the subject's body, in which the lumen is disposed, is acquired, during movement of the endoluminal device through the lumen. Locations at which the one or more radiopaque portions of the endoluminal device were imaged during the movement of the endoluminal device through the lumen are identified, by analyzing the sequence of radiographic images. A set of locations at which the one or more radiopaque portions were disposed during the movement of the endoluminal device through the lumen is defined, and an endoluminal path of the device through the lumen is estimated based upon the set of locations. Other applications are also described.

Recent studies in computer vision have shown that, while practically invisible to a human observer, skin color changes due to blood flow can be captured on face videos and, surprisingly, be used to estimate the heart rate (HR). While considerable progress has been made in the last few years, still many issues remain open. In particular, state-of-the-art approaches are not robust enough to operate in natural conditions (e.g. in case of spontaneous movements, facial expressions, or illumination changes). Opposite to previous approaches that estimate the HR by processing all the skin pixels inside a fixed region of interest, we introduce a strategy to dynamically select face regions useful for robust HR estimation. The present approach, inspired by recent advances on matrix completion theory, allows us to predict the HR while simultaneously discover the best regions of the face to be used for estimation. Thorough experimental evaluation conducted on public benchmarks suggests that the proposed approach significantly outperforms state-of-the-art HR estimation methods in naturalistic conditions.

An information processing apparatus includes at least one processor that is configured to: acquire a low-energy image captured by a radiography apparatus by emitting radiation having first energy to a subject into which a contrast medium has been injected, and each of a plurality of high-energy images captured by the radiography apparatus at different timings by emitting radiation having second energy higher than the first energy to the subject into which the contrast medium has been injected, and generate a plurality of difference images showing a difference between the low-energy image and each of the plurality of high-energy images.

A method for precisely applying chemicals targeted by digital maps developed from remotely sensed data, including: obtaining EOS data through a growing season of a crop growing in a field; processing the EOS data to reflectance values, removing error-inducing effects of atmospheric alteration from the processed EOS data; calculating from the processed EOS data a crop performance index that indicates one or more poor performing area of the field; generating one or more maps of the crop performance index to allow a user to determine whether each of the one or more poor performing areas of the field are due to biological pests instead of topographic or soil constraints in discrete locations of the field, guiding the user to the one or more poor performing areas of the field using the one or more maps to allow the user to scout the one or more poor performing areas of the field to confirm and identify the biological pests; and providing guidance for a chemical application at the one or more poor performing areas that were confirmed as having the biological pests. Other embodiments are provided.

A system and method for measuring light within a boundary of an image includes an instrument configured to capture the image; a display; a user input device; and a processor configured to: receive the image from the instrument; obtains a light intensity value of each image pixel around the boundary of the image, wherein at least one light illuminator on the instrument stimulates the each image pixel, wherein the each image pixel reflects a magnitude of light that is captured by one or more spotting devices on the instrument; create a pixel intensity map along the boundary of the image that relates to the light intensity value of the each image pixel; and present a graphical user interface via the display based on the pixel intensity map.

A roof mounted module for a vehicle includes an imager housing in secure engagement with a roof of the vehicle. The imager housing defines a lateral aperture and a vertical aperture. An imager is disposed in the imager housing and is in communication with the lateral aperture. An antenna housing is removably coupled to the imager housing and is in communication with the vehicle via a data connection that extends through the vertical aperture.

Disclosed is a method for detecting positions of body tissues and an apparatus using the method. The apparatus according to the present invention comprises a surgery information storage unit storing an examined first image associated with a target bone of surgery, a position measuring unit measuring position values of multiple points on a surface of the target bone of surgery before and after cutting, and a registration control unit for acquiring a second image regarding the remained bone after cutting by applying the shape of the bone changed according to the progression of bone cutting to the first image, and for performing position registration with respect to the second image by using the position values of multiple points on surface of the target bone of surgery after cutting, which is measured by the position measuring unit.